Computer Systems That Learn: Classification and Prediction Methods from Statistics, Neural Nets, Machine Learning and Expert Systems (Machine Learning Series)
This book is a practical guide to classification learning systems and their applications. Get and download textbook Computer Systems That Learn: Classification and Prediction Methods from Statistics, Neural Nets, Machine Learning and Expert Systems (Machine Learning Series) for free
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These computer programs learn from sample data and make predictions for new cases, sometimes exceeding the performance of humans.
Practical learning systems from statistical pattern recognition, neural networks, and machine learning are presented. The authors examine prominent methods from each area, using an engineering approach and taking the practitioner's viewpoint. Intuitive explanations with a minimum of mathematics make the material accessible to anyone--regardless of experience or special interests.
The underlying concepts of the learning methods are discussed with fully worked-out examples: their strengths and weaknesses, and the estimati Computer Systems That Learn new edition
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Computer Systems That Learn Textbook
These computer programs learn from sample data and make predictions for new cases, sometimes exceeding the performance of humans.
Practical learning systems from statistical pattern recognition, neural networks, and machine learning are presented. The authors examine prominent methods from each area, using an engineering approach and taking the practitioner's viewpoint. Intuitive explanations with a minimum of mathematics make the material accessible to anyone--regardless of experience or special interests
These computer programs learn from sample data and make predictions for new cases, sometimes exceeding the performance of humans.
Practical learning systems from statistical pattern recognition, neural networks, and machine learning are presented. The authors examine prominent methods from each area, using an engineering approach and taking the practitioner's viewpoint. Intuitive explanations with a minimum of mathematics make the material accessible to anyone--regardless of experience or special interests.
The underlying concepts of the learning methods are discussed with fully worked-out examples: their strengths and weaknesses, and the estimati
